溶剂对分子印迹聚合物分子识别能力的影响：实验研究与计算量子化学分析

以茶碱为印迹分子，甲基丙烯酸为功能单体，二甲基丙烯酸乙二醇酯为交联剂，以氯仿、二甲基亚砜和四氢呋喃为溶剂，合成了分子印迹聚合物并测定了其对茶碱分子的识别能力，实验结果显示，在氯仿中合成的MIPs的分子识别性能最佳.综合Scatchard分析吸附行为、¹H NMR测定氢键以及量子化学中的密度泛函计算印迹分子和单体分子的溶剂化能等方法，研究聚合反应的溶剂体系对于印迹聚合物分子识别能力的影响及其作用机制.计算结果显示：采用与印迹分子和单体相互作用力较弱的溶剂体系所合成的印迹聚合物具有较高的分子识别性能.这与¹H NMR分析结果和吸附测定实验结果具有一致性.上述结果表明，溶剂对于分子印迹聚合物的分子识别性能具有重要的影响，而计算量子化学分析对于分子印迹介质合成时的溶剂体系选取和优化具有很好的指导作用.     

Overcoming the inadequacies or limitations of experimental structures as drug targets by using computational modeling tools and molecular dynamics simulations

X-ray crystallography, NMR spectroscopy, and cryoelectron microscopy stand out as powerful tools that enable us to obtain atomic detail about biomolecules that can be potentially targeted by drugs. This knowledge is essential if virtual screening or structure-based ligand-design methods are going to be used in drug discovery. However, the macromolecule of interest is not always amenable to these types of experiment or, as is often the case, the conformation found experimentally cannot be used directly for docking studies because of significant changes between apo and bound forms. Furthermore, sometimes the desired insight into the binding mechanism cannot be gained because the structure of the ligand-receptor complex, not having been time-resolved, represents the endpoint of the binding process and therefore retains little or no information about the intermediate stages that led to its creation. Molecular dynamics (MD) simulations are routinely applied these days to the study of biomolecular systems with the aims of sampling configuration space more efficiently and getting a better understanding of the factors that determine structural stability and relevant biophysical and biochemical processes such as protein folding, ligand binding, and enzymatic reactions. This field has matured significantly in recent years, and strategies have been devised (for example activated, steered, or targeted MD) that allow the calculated trajectories to be biased in attempts to properly shape a ligand binding pocket or simulate large-scale motions involving one or more protein domains. On the other hand, low-frequency motions can be simulated quite inexpensively by calculation of normal modes which allow the investigation of alternative receptor conformations. Selected examples in which these methods have been applied to several medicinal chemistry and in silico pharmacology endeavors are presented.